Cambricon’s MLU chips are not merely processors; they represent China’s strategic approach to scalable and efficient AI acceleration across cloud, edge, and data center settings.
Through this instructor-led training, engineers and AI developers navigate the Cambricon stack, covering the full spectrum from deploying deep learning models to optimizing performance on MLU hardware.
Courses are available as live online training conducted over interactive remote desktop, or as onsite sessions in Sofia, where practical labs replicate the real-world AI challenges that Cambricon technology is engineered to address.
Whether you are expanding an AI lab or preparing a data center team for the future, onsite sessions can be hosted at your facility in Sofia or at a NobleProg training center built for immersive technical learning.
Also known as Cambricon AI, MLU accelerator, or Machine Learning Unit, this training supports teams developing AI infrastructure beyond the standard GPU approach.
NobleProg – Your Local Training Provider
Crystal Business Center
ул. "Осогово" 40, Sofia, Bulgaria, 1303
Crystal Business Center is located in the central part of Sofia, on the corner of "Osogovo" street. and "Todor Aleksandrov" blvd. The building is easily accessible by metro (only 50 m from Opalchenska station) and other public transport. Its total area is 8000 sq.m. The office area is 6171 sq.m.
Optimize AI workloads on Ascend, Biren, and Cambricon with this hands-on training in Sofia. Learn to benchmark models, identify bottlenecks, and apply graph, kernel, and operator-level optimizations. Tune deployment pipelines to enhance throughput and latency across these leading platforms.
Migrate CUDA applications to Chinese GPU architectures like Huawei Ascend and Biren in Sofia. This instructor-led course guides advanced programmers through code translation and performance optimization, covering hands-on labs for porting CUDA codebases to new SDKs.
This instructor-led live training in Sofia equips developers with the skills to build and deploy AI models using BANGPy and Neuware on Cambricon MLUs. Participants will configure environments, develop optimized models, and integrate MLU acceleration into edge and data center applications.
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